Why Use AI in Advertising? 5 Benefits for Marketers

Artificial intelligence is changing how marketers plan, create, test, and adapt advertising campaigns. AI can help generate copy and visual concepts, create variations for different audiences, analyze campaign data, and speed up parts of the creative workflow.

But using AI in advertising is not simply about replacing human work with automated tools. The most practical approach is to use AI where it saves time, expands creative options, or makes experimentation easier while keeping people responsible for strategy, brand consistency, accuracy, and final approval.

Key Takeaways

• AI-generated advertising can include text, images, video, audio, and other campaign assets created or modified with AI.
• AI can shorten parts of the creative production process, especially when marketers need multiple concepts or variations.
• Lower production costs are possible in some workflows, but AI does not guarantee that an entire campaign will be cheaper.
• AI can support personalization and A/B testing, but useful results depend on data quality, audience segmentation, and human oversight.
• Consumers have mixed feelings about AI advertising, with significant discomfort around AI-generated brand ambassadors and product imagery.
• AI works best as part of a human-led advertising workflow rather than as a replacement for creative strategy.
• Photo editors such as Luminar can complement AI marketing workflows by helping teams prepare, clean up, resize, or adapt visual assets for different advertising formats.

What Is AI-Generated Advertising?

AI-generated advertising is advertising content created or substantially modified with artificial intelligence. Depending on the workflow, AI can be used to generate advertising copy, images, video, audio, product concepts, or variations of existing creative assets.

AI can also support other parts of advertising that are not strictly content generation. For example, marketers can use AI-assisted systems to analyze audiences, predict performance, test creative variations, or optimize campaign delivery.

It is useful to distinguish between AI-assisted advertising and fully AI-generated advertising. In an AI-assisted workflow, people may use AI for specific tasks while creating and approving the final campaign themselves. A fully AI-generated advertisement relies much more heavily on AI for its creative production.

Approach	Typical use	Human involvement
AI-assisted advertising	Brainstorming, editing, image variations, audience analysis	High
AI-generated creative	Generating copy, images, audio, or video	Moderate to high
Highly automated advertising	Generating and testing large numbers of variations	Required for oversight and approval

The distinction matters because AI can accelerate production without eliminating the need for creative direction, fact-checking, brand review, and ethical judgment.

How Do Consumers Perceive AI-Generated Advertising?

Consumers do not have a uniformly positive or negative attitude toward AI advertising.

A 2024 YouGov survey covering 17 international markets found that 47% of respondents were uncomfortable with brands using AI to generate product images, while 48% were uncomfortable with AI editing product images instead of graphic designers. Virtual AI-generated brand ambassadors produced even more concern: 51% of respondents said they were uncomfortable with this use. At the same time, 39% said they were comfortable with both AI-generated and AI-edited product images.

Transparency can also matter. Among consumers who were comfortable with AI being used in advertising, a majority said brands should disclose AI use in several of the scenarios included in the YouGov research.

This suggests an important principle for marketers: using AI is not automatically a problem, but hiding how it is used can affect audience trust. The appropriate approach depends on the type of content, the expectations of the audience, and the context in which the advertisement appears.

5 Benefits of Using AI in Advertising Campaigns

1. Faster Creative Production

One of the clearest benefits of AI in advertising is speed.

Traditional campaign production can involve copywriters, designers, photographers, videographers, editors, and multiple rounds of approvals. AI tools can reduce the time needed for some of these intermediate tasks.

For example, a marketer might use AI to:

• Generate several headline ideas.
• Create initial visual concepts.
• Adapt copy for different audience segments.
• Produce alternative layouts or image concepts.
• Summarize campaign performance.
• Prepare variations for testing.

The goal is not necessarily to eliminate the creative team. Instead, AI can reduce the amount of repetitive work between the initial idea and the finished campaign.

A useful workflow is to let AI produce a broad set of options and then have marketers select, edit, fact-check, and refine the strongest ones.

2. More Efficient Use of the Advertising Budget

AI can reduce costs in some areas of advertising production, particularly when a campaign requires many creative variations.

A frequently cited example is Kalshi’s AI-generated commercial that aired during the 2025 NBA Finals. According to reporting by The Verge, the production cost was about $2,000, and the creator said the commercial was produced using Google’s Veo 3 along with AI-assisted scripting and conventional editing tools. The production reportedly involved hundreds of generated clips before the final selection.

The example illustrates the potential cost advantage of AI-assisted production, but it should not be treated as a universal benchmark. AI-generated campaigns can still require substantial spending on strategy, editing, talent, media placement, software, revisions, and human quality control.

A better way to think about the financial benefit is this: AI can lower the cost of experimentation and asset production in certain workflows. That can make it easier for smaller teams to explore more creative directions without commissioning every variation from scratch.

3. Easier Personalization and Creative Variation

Personalized advertising can become difficult when every audience segment requires separate creative assets.

AI can help marketers produce variations of headlines, descriptions, images, or other campaign elements for different audiences. Instead of creating every variation manually, teams can use AI to generate starting points and then review them before publication.

For example, an ecommerce company could develop different creative directions for:

• First-time visitors.
• Returning customers.
• Different product categories.
• Different geographic markets.
• Different stages of the buying journey.

However, AI does not make personalization completely automatic. Marketers still need appropriate data, clear audience definitions, consistent brand guidelines, and careful review of generated content.

This is particularly important when personalisation involves customer data. AI should not become an excuse to collect or use information without considering privacy, consent, security, and applicable regulations.

4. More Creative Testing

AI can make it easier to explore multiple creative ideas before committing to a final campaign.

Instead of producing one headline and one image, a team can create several variations and test them against defined performance metrics. These might include click-through rate, conversion rate, engagement, or another campaign-specific goal.

For example, a marketer could test:

Variable	Example variations
Headline	Product-focused / benefit-focused / question
Image	Product close-up / lifestyle scene / human subject
Call to action	Shop now / See options / Get started
Composition	Subject centered / subject to one side / close-up
Message	Price / convenience / product feature

The important point is that AI can help increase the number of ideas available for testing, but it cannot determine success on its own. Performance data still needs to be interpreted in context.

AI-generated creative can also introduce unexpected ideas that a team may not have considered initially. Those ideas can then become starting points for human-led creative development.

5. Greater Scalability Across Formats

Advertising campaigns rarely use only one image or one piece of copy. The same campaign may need assets for social media, websites, display advertising, email, mobile screens, and different aspect ratios.

AI can help teams adapt existing creative concepts to these requirements more efficiently.

For image-based campaigns, this is where an AI photo editor can complement a broader advertising workflow. Luminar provides tools for adjusting and preparing visual assets, while generative features such as GenErase can remove distracting elements from an image and GenExpand can extend the image beyond its original frame.

GenExpand can be particularly useful when an existing photograph needs additional space for a different composition or advertising layout. This can reduce the need to reshoot an image simply because the original framing does not fit a particular format.

When generative editing substantially changes the original image, however, marketers should consider whether the resulting visual still accurately represents the product or situation being advertised.

How to Use AI in Advertising Responsibly

The benefits of AI advertising come with several practical considerations. A fast workflow is useful only if the final advertisement is accurate, appropriate, and consistent with the brand.

Keep Human Review in the Workflow

AI-generated text and images can contain factual errors, visual inconsistencies, or details that do not match the actual product.

Before publishing an AI-assisted advertisement, check:

• Product specifications and prices.
• Names, dates, and other factual claims.
• Brand terminology.
• Logos and visual identity.
• People, objects, and product appearance in generated images.
• Copyright and licensing requirements.
• Whether the final image accurately represents the product.

Be Careful With Product Images

Generative AI can create attractive visuals, but advertising has a higher accuracy requirement than purely conceptual content.

If an AI-generated image changes the appearance, size, color, functionality, or other important characteristic of a product, consumers could receive a misleading impression.

For product advertising, AI is often most useful when it supports the creative process without inventing characteristics that the real product does not have.

Consider Disclosure and Audience Expectations

Consumer expectations vary depending on the type of AI use.

Using AI to brainstorm a headline is very different from creating a completely synthetic spokesperson or replacing a real product photograph with an AI-generated image. The more extensively AI changes the content, the more important transparency and careful review can become.

YouGov’s research suggests that many consumers who are comfortable with AI advertising still believe brands should disclose certain forms of AI use.

Pros and Cons of AI in Advertising

Pros	Cons
Speeds up parts of creative production	Generated content can contain errors
Makes creative experimentation easier	Quality can vary between generations
Can reduce some production costs	AI does not guarantee lower campaign costs
Helps create multiple creative variations	Large numbers of variations require testing and review
Can support different formats and audiences	Poorly controlled personalization can create privacy and brand risks
Can expand existing visual assets	Generative edits may make images less accurate

Conclusion

AI in advertising is most useful when it helps marketers move faster, explore more ideas, test creative variations, and adapt visual assets without adding unnecessary production work.

The strongest approach is not to automate everything. Instead, identify the parts of the advertising workflow where AI provides a clear advantage and keep human oversight where accuracy, brand identity, and audience trust matter most.

For image-heavy campaigns, tools such as Luminar can complement this workflow by helping marketers refine, clean up, and adapt existing visual assets while keeping creative decisions under human control.

Frequently Asked Questions